The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models

Ivashchenko Sergey, Mutschler Willi


Abstract
The decisions a researcher makes at the model building stage are crucial for parameter identification. This paper contains a number of applied tips for solving identifiability problems and improving the strength of DSGE model parameter identification by fine-tuning the (1) choice of observables, (2) functional specifications, (3) model features and (4) choice of structural shocks. We offer a formal approach based on well-established diagnostics and indicators to uncover and address both theoretical (yes/no) identifiability issues and weak identification from a Bayesian perspective. The concepts are illustrated by two exemplary models that demonstrate the identification properties of different investment adjustment cost specifications and output-gap definitions.

Keywords
DSGE models; Local identification; Weak identification; Investment adjustment costs; Output-gap; Observables



Publication type
Research article (journal)

Peer reviewed
Yes

Publication status
online first

Year
2019

Journal
Economic Modelling

Volume
2019

Language
English

ISSN
0264-9993

DOI